Section 5 - The third of five verbs: filter

Logical operators

R comes with a set of logical operators that you can use inside filter():

x < y, TRUE if x is less than y
x <= y, TRUEifxis less than or equal toyx == y, TRUE if x equals y
x != y, TRUEifxdoes not equalyx >= y, TRUE if x is greater than or equal to y
x > y, TRUEifxis greater thanyx %in% c(a, b, c),TRUEifxis in the vectorc(a, b, c)`

The following example filters df such that only the observations for which a is positive, are kept:

filter(df, a > 0)

# Load the hflights package
library(hflights)

hflights_df <- hflights[sample(nrow(hflights), 720), ] 
hflights <- as_tibble(hflights)

# All flights that traveled 3000 miles or more
filter(hflights, Distance >= 3000) %>% glimpse()
## Observations: 527
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DayofMonth        <int> 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, ...
## $ DayOfWeek         <int> 1, 7, 6, 5, 4, 3, 2, 1, 7, 6, 5, 4, 3, 2, 1,...
## $ DepTime           <int> 924, 925, 1045, 1516, 950, 944, 924, 1144, 9...
## $ ArrTime           <int> 1413, 1410, 1445, 1916, 1344, 1350, 1337, 16...
## $ UniqueCarrier     <chr> "CO", "CO", "CO", "CO", "CO", "CO", "CO", "C...
## $ FlightNum         <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ TailNum           <chr> "N69063", "N76064", "N69063", "N77066", "N76...
## $ ActualElapsedTime <int> 529, 525, 480, 480, 474, 486, 493, 501, 489,...
## $ AirTime           <int> 492, 493, 459, 463, 455, 471, 473, 464, 466,...
## $ ArrDelay          <int> 23, 20, 55, 326, -6, 0, -13, 135, -15, -10, ...
## $ DepDelay          <int> -1, 0, 80, 351, 25, 19, -1, 139, 1, 17, 3, 1...
## $ Origin            <chr> "IAH", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "HNL", "HNL", "HNL", "HNL", "HNL", "HNL", "H...
## $ Distance          <int> 3904, 3904, 3904, 3904, 3904, 3904, 3904, 39...
## $ TaxiIn            <int> 6, 13, 4, 7, 4, 5, 5, 7, 6, 3, 6, 4, 6, 4, 5...
## $ TaxiOut           <int> 31, 19, 17, 10, 15, 10, 15, 30, 17, 10, 19, ...
## $ Cancelled         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
## $ CancellationCode  <chr> "", "", "", "", "", "", "", "", "", "", "", ...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,...
# All flights flown by one of JetBlue, Southwest, or Delta
filter(hflights, UniqueCarrier %in% c("JetBlue", "Southwest", "Delta")) %>% glimpse()
## Observations: 0
## Variables: 21
## $ Year              <int> 
## $ Month             <int> 
## $ DayofMonth        <int> 
## $ DayOfWeek         <int> 
## $ DepTime           <int> 
## $ ArrTime           <int> 
## $ UniqueCarrier     <chr> 
## $ FlightNum         <int> 
## $ TailNum           <chr> 
## $ ActualElapsedTime <int> 
## $ AirTime           <int> 
## $ ArrDelay          <int> 
## $ DepDelay          <int> 
## $ Origin            <chr> 
## $ Dest              <chr> 
## $ Distance          <int> 
## $ TaxiIn            <int> 
## $ TaxiOut           <int> 
## $ Cancelled         <int> 
## $ CancellationCode  <chr> 
## $ Diverted          <int>
# All flights where taxiing took longer than flying
filter(hflights, (TaxiIn + TaxiOut) > AirTime) %>% glimpse()
## Observations: 1,389
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DayofMonth        <int> 24, 30, 24, 10, 31, 31, 31, 31, 30, 30, 30, ...
## $ DayOfWeek         <int> 1, 7, 1, 1, 1, 1, 1, 1, 7, 7, 7, 7, 7, 7, 7,...
## $ DepTime           <int> 731, 1959, 1621, 941, 1301, 2113, 1434, 900,...
## $ ArrTime           <int> 904, 2132, 1749, 1113, 1356, 2215, 1539, 100...
## $ UniqueCarrier     <chr> "AA", "AA", "AA", "AA", "CO", "CO", "CO", "C...
## $ FlightNum         <int> 460, 533, 1121, 1436, 241, 1533, 1541, 1583,...
## $ TailNum           <chr> "N545AA", "N455AA", "N484AA", "N591AA", "N14...
## $ ActualElapsedTime <int> 93, 93, 88, 92, 55, 62, 65, 66, 64, 84, 80, ...
## $ AirTime           <int> 42, 43, 43, 45, 27, 30, 30, 32, 31, 40, 37, ...
## $ ArrDelay          <int> 29, 12, 4, 48, -2, 20, 15, 10, 10, 54, 16, 1...
## $ DepDelay          <int> 11, -6, -9, 31, -4, 13, 4, 0, -1, 39, 2, -4,...
## $ Origin            <chr> "IAH", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "DFW", "DFW", "DFW", "DFW", "AUS", "AUS", "A...
## $ Distance          <int> 224, 224, 224, 224, 140, 140, 140, 140, 140,...
## $ TaxiIn            <int> 14, 10, 10, 27, 5, 7, 5, 5, 6, 10, 6, 4, 6, ...
## $ TaxiOut           <int> 37, 40, 35, 20, 23, 25, 30, 29, 27, 34, 37, ...
## $ Cancelled         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
## $ CancellationCode  <chr> "", "", "", "", "", "", "", "", "", "", "", ...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...

Combining tests using boolean operators

R also comes with a set of boolean operators that you can use to combine multiple logical tests into a single test. These include & (and), | (or), and ! (not). Instead of using the & operator, you can also pass several logical tests to filter(), separated by commas. The following two calls are completely equivalent:

filter(df, a > 0 & b > 0)
filter(df, a > 0, b > 0)

Next, is.na() will also come in handy. This example keeps the observations in df for which the variable x is not NA:

filter(df, !is.na(x))

# All flights that departed before 5am or arrived after 10pm
filter(hflights, DepTime < 500 | ArrTime > 2200) %>% glimpse()
## Observations: 27,799
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DayofMonth        <int> 4, 14, 10, 26, 30, 9, 31, 31, 31, 31, 31, 31...
## $ DayOfWeek         <int> 2, 5, 1, 3, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DepTime           <int> 2100, 2119, 1934, 1905, 1856, 1938, 1919, 21...
## $ ArrTime           <int> 2207, 2229, 2235, 2211, 2209, 2228, 2231, 23...
## $ UniqueCarrier     <chr> "AA", "AA", "AA", "AA", "AA", "AS", "CO", "C...
## $ FlightNum         <int> 533, 533, 1294, 1294, 1294, 731, 190, 209, 2...
## $ TailNum           <chr> "N4XGAA", "N549AA", "N3BXAA", "N3BXAA", "N3C...
## $ ActualElapsedTime <int> 67, 70, 121, 126, 133, 290, 132, 268, 141, 1...
## $ AirTime           <int> 42, 45, 107, 111, 108, 253, 107, 256, 121, 1...
## $ ArrDelay          <int> 47, 69, 80, 56, 54, 78, -12, -15, -18, -10, ...
## $ DepDelay          <int> 55, 74, 99, 70, 61, 73, -1, -7, 0, 8, -1, 5,...
## $ Origin            <chr> "IAH", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "DFW", "DFW", "MIA", "MIA", "MIA", "SEA", "M...
## $ Distance          <int> 224, 224, 964, 964, 964, 1874, 964, 1825, 10...
## $ TaxiIn            <int> 3, 5, 3, 5, 7, 5, 5, 4, 5, 6, 4, 18, 4, 7, 9...
## $ TaxiOut           <int> 22, 20, 11, 10, 18, 32, 20, 8, 15, 9, 18, 22...
## $ Cancelled         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
## $ CancellationCode  <chr> "", "", "", "", "", "", "", "", "", "", "", ...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
# All flights that departed late but arrived ahead of schedule
filter(hflights, DepDelay > 0, ArrDelay < 0) %>% glimpse()
## Observations: 27,712
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DayofMonth        <int> 2, 5, 18, 18, 12, 13, 26, 1, 10, 12, 15, 17,...
## $ DayOfWeek         <int> 7, 3, 2, 2, 3, 4, 3, 6, 1, 3, 6, 1, 4, 7, 6,...
## $ DepTime           <int> 1401, 1405, 1408, 721, 2015, 2020, 2009, 163...
## $ ArrTime           <int> 1501, 1507, 1508, 827, 2113, 2116, 2103, 173...
## $ UniqueCarrier     <chr> "AA", "AA", "AA", "AA", "AA", "AA", "AA", "A...
## $ FlightNum         <int> 428, 428, 428, 460, 533, 533, 533, 1121, 112...
## $ TailNum           <chr> "N557AA", "N492AA", "N507AA", "N558AA", "N55...
## $ ActualElapsedTime <int> 60, 62, 60, 66, 58, 56, 54, 65, 61, 68, 64, ...
## $ AirTime           <int> 45, 44, 42, 46, 39, 44, 39, 37, 41, 44, 48, ...
## $ ArrDelay          <int> -9, -3, -2, -8, -7, -4, -17, -9, -5, -6, -9,...
## $ DepDelay          <int> 1, 5, 8, 1, 10, 15, 4, 1, 9, 1, 2, 2, 4, 5, ...
## $ Origin            <chr> "IAH", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "DFW", "DFW", "DFW", "DFW", "DFW", "DFW", "D...
## $ Distance          <int> 224, 224, 224, 224, 224, 224, 224, 224, 224,...
## $ TaxiIn            <int> 6, 9, 7, 7, 9, 4, 9, 16, 8, 5, 5, 10, 10, 9,...
## $ TaxiOut           <int> 9, 9, 11, 13, 10, 8, 6, 12, 12, 19, 11, 11, ...
## $ Cancelled         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
## $ CancellationCode  <chr> "", "", "", "", "", "", "", "", "", "", "", ...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
# All flights that were cancelled after being delayed
filter(hflights, DepDelay > 0, Cancelled == 1) %>% glimpse()
## Observations: 40
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 4, 4, 4, 4, 4,...
## $ DayofMonth        <int> 26, 11, 19, 7, 4, 8, 2, 9, 1, 31, 4, 8, 21, ...
## $ DayOfWeek         <int> 3, 2, 3, 5, 5, 2, 3, 3, 2, 4, 1, 5, 4, 1, 1,...
## $ DepTime           <int> 1926, 1100, 1811, 2028, 1638, 1057, 802, 904...
## $ ArrTime           <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ UniqueCarrier     <chr> "CO", "US", "XE", "XE", "AA", "CO", "XE", "X...
## $ FlightNum         <int> 310, 944, 2376, 3050, 1121, 408, 2189, 2605,...
## $ TailNum           <chr> "N77865", "N452UW", "N15932", "N15912", "N53...
## $ ActualElapsedTime <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ AirTime           <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ ArrDelay          <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ DepDelay          <int> 26, 135, 6, 73, 8, 187, 2, 4, 28, 156, 42, 5...
## $ Origin            <chr> "IAH", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "EWR", "CLT", "ICT", "JAX", "DFW", "EWR", "D...
## $ Distance          <int> 1400, 913, 542, 817, 224, 1400, 217, 217, 68...
## $ TaxiIn            <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ TaxiOut           <int> NA, NA, NA, 19, 19, NA, NA, NA, 19, NA, NA, ...
## $ Cancelled         <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ CancellationCode  <chr> "B", "B", "B", "A", "A", "A", "B", "B", "A",...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...

Blend together what you’ve learned!

So far, you have learned three data manipulation functions in the dplyr package. Time for a summarizing exercise. You will generate a new dataset from the `hflights dataset that contains some useful information on flights that hadJFK airportas their destination. You will needselect(),mutate()andfilter()`.

# Select the flights that had JFK as their destination: c1
c1 <- filter(hflights, Dest == "JFK")

# Combine the Year, Month and DayofMonth variables to create a Date column: c2
c2 <- mutate(c1, Date = paste(Year, Month, DayofMonth, sep='-'))

# Print out a selection of columns of c2
select(c2, Date, DepTime, ArrTime, TailNum)
## # A tibble: 695 x 4
##    Date     DepTime ArrTime TailNum
##    <chr>      <int>   <int> <chr>  
##  1 2011-1-1     654    1124 N324JB 
##  2 2011-1-1    1639    2110 N324JB 
##  3 2011-1-2     703    1113 N324JB 
##  4 2011-1-2    1604    2040 N324JB 
##  5 2011-1-3     659    1100 N229JB 
##  6 2011-1-3    1801    2200 N206JB 
##  7 2011-1-4     654    1103 N267JB 
##  8 2011-1-4    1608    2034 N267JB 
##  9 2011-1-5     700    1103 N708JB 
## 10 2011-1-5    1544    1954 N644JB 
## # ... with 685 more rows

Recap on select, mutate and filter

With select(), mutate() and filter(), you can already reveal interesting information from a dataset. Through a combination of these expressions or by the use of a one-liner, try to answer the following question:

How many weekend flights flew a distance of more than 1000 miles but had a total taxiing time below 15 minutes?

filter(hflights, DayOfWeek %in% c(6,7), Distance > 1000, (TaxiIn + TaxiOut) < 15) %>% glimpse()
## Observations: 1,739
## Variables: 21
## $ Year              <int> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 20...
## $ Month             <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## $ DayofMonth        <int> 23, 30, 30, 29, 23, 23, 23, 22, 16, 16, 16, ...
## $ DayOfWeek         <int> 7, 7, 7, 6, 7, 7, 7, 6, 7, 7, 7, 7, 7, 7, 7,...
## $ DepTime           <int> 1535, 851, 2234, 1220, 847, 1224, 931, 942, ...
## $ ArrTime           <int> 1933, 1230, 2, 1353, 1213, 1345, 1045, 1340,...
## $ UniqueCarrier     <chr> "B6", "CO", "CO", "CO", "CO", "CO", "CO", "C...
## $ FlightNum         <int> 624, 1058, 1717, 1620, 1058, 1629, 1723, 1, ...
## $ TailNum           <chr> "N599JB", "N39726", "N38417", "N87512", "N16...
## $ ActualElapsedTime <int> 178, 159, 208, 153, 146, 201, 194, 478, 288,...
## $ AirTime           <int> 164, 145, 195, 139, 134, 188, 181, 465, 275,...
## $ ArrDelay          <int> -27, -13, 89, 19, -30, -27, -28, -10, 12, -1...
## $ DepDelay          <int> 0, -2, 94, 45, -6, -1, -5, 17, -2, -5, 3, -1...
## $ Origin            <chr> "HOU", "IAH", "IAH", "IAH", "IAH", "IAH", "I...
## $ Dest              <chr> "JFK", "DCA", "SAN", "PHX", "DCA", "SNA", "O...
## $ Distance          <int> 1428, 1208, 1303, 1009, 1208, 1347, 1334, 39...
## $ TaxiIn            <int> 6, 3, 3, 5, 4, 4, 3, 3, 5, 3, 3, 4, 3, 6, 4,...
## $ TaxiOut           <int> 8, 11, 10, 9, 8, 9, 10, 10, 8, 10, 9, 10, 11...
## $ Cancelled         <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
## $ CancellationCode  <chr> "", "", "", "", "", "", "", "", "", "", "", ...
## $ Diverted          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...

answer: 155 flights !

Section 6 - Almost there: the arrange verb

Arranging your data

arrange() can be used to rearrange rows according to any type of data. If you pass arrange() a character variable, for example, R will rearrange the rows in alphabetical order according to values of the variable. If you pass a factor variable, R will rearrange the rows according to the order of the levels in your factor (running levels() on the variable reveals this order).

dtc has already been defined on the right. It’s up to you to write some arrange() expressions to display its contents appropriately!

# Definition of dtc
dtc <- filter(hflights, Cancelled == 1, !is.na(DepDelay))

# Arrange dtc by departure delays
arrange(dtc, DepDelay) %>%
  head(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "center", , font_size = 11) %>%
  row_spec(0, bold = T, color = "white", background = "#3f7689")
Year Month DayofMonth DayOfWeek DepTime ArrTime UniqueCarrier FlightNum TailNum ActualElapsedTime AirTime ArrDelay DepDelay Origin Dest Distance TaxiIn TaxiOut Cancelled CancellationCode Diverted
2011 7 23 6 605 NA F9 225 N912FR NA NA NA -10 HOU DEN 883 NA 10 1 A 0
2011 1 17 1 916 NA XE 3068 N13936 NA NA NA -9 IAH HRL 295 NA NA 1 B 0
2011 12 1 4 541 NA US 282 N840AW NA NA NA -9 IAH PHX 1009 NA NA 1 A 0
2011 10 12 3 2022 NA MQ 3724 N539MQ NA NA NA -8 IAH LAX 1379 NA NA 1 A 0
2011 7 29 5 1424 NA CO 1079 N14628 NA NA NA -6 IAH ORD 925 NA 13 1 A 0
2011 9 29 4 1639 NA OO 2062 N724SK NA NA NA -6 IAH ATL 689 NA NA 1 B 0
2011 2 9 3 555 NA MQ 3265 N613MQ NA NA NA -5 HOU DFW 247 NA 11 1 A 0
2011 5 9 1 715 NA OO 1177 N758SK NA NA NA -5 IAH DTW 1076 NA 17 1 A 0
2011 1 20 4 1413 NA UA 552 N509UA NA NA NA -4 IAH IAD 1190 NA NA 1 A 0
2011 1 17 1 831 NA WN 1 N714CB NA NA NA -4 HOU HRL 276 NA 8 1 B 0 
# Arrange dtc so that cancellation reasons are grouped
arrange(dtc, CancellationCode) %>%
  head(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "center", , font_size = 11) %>%
  row_spec(0, bold = T, color = "white", background = "#3f7689")
Year Month DayofMonth DayOfWeek DepTime ArrTime UniqueCarrier FlightNum TailNum ActualElapsedTime AirTime ArrDelay DepDelay Origin Dest Distance TaxiIn TaxiOut Cancelled CancellationCode Diverted
2011 1 20 4 1413 NA UA 552 N509UA NA NA NA -4 IAH IAD 1190 NA NA 1 A 0
2011 1 7 5 2028 NA XE 3050 N15912 NA NA NA 73 IAH JAX 817 NA 19 1 A 0
2011 2 4 5 1638 NA AA 1121 N537AA NA NA NA 8 IAH DFW 224 NA 19 1 A 0
2011 2 8 2 1057 NA CO 408 N11641 NA NA NA 187 IAH EWR 1400 NA NA 1 A 0
2011 2 1 2 1508 NA OO 5812 N959SW NA NA NA 28 IAH ATL 689 NA 19 1 A 0
2011 2 21 1 2257 NA OO 1111 N778SK NA NA NA -3 IAH AUS 140 NA NA 1 A 0
2011 2 9 3 555 NA MQ 3265 N613MQ NA NA NA -5 HOU DFW 247 NA 11 1 A 0
2011 3 18 5 727 NA UA 109 N469UA NA NA NA -3 IAH DEN 862 NA NA 1 A 0
2011 4 4 1 1632 NA DL 8 N600TR NA NA NA 42 IAH ATL 689 NA NA 1 A 0
2011 4 8 5 1608 NA WN 4 N365SW NA NA NA 548 HOU DAL 239 NA NA 1 A 0 
# Arrange dtc according to carrier and departure delays
arrange(dtc, UniqueCarrier, DepDelay) %>%
  head(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "center", , font_size = 11) %>%
  row_spec(0, bold = T, color = "white", background = "#3f7689")
Year Month DayofMonth DayOfWeek DepTime ArrTime UniqueCarrier FlightNum TailNum ActualElapsedTime AirTime ArrDelay DepDelay Origin Dest Distance TaxiIn TaxiOut Cancelled CancellationCode Diverted
2011 8 18 4 1808 NA AA 1294 N3FLAA NA NA NA 3 IAH MIA 964 NA NA 1 A 0
2011 2 4 5 1638 NA AA 1121 N537AA NA NA NA 8 IAH DFW 224 NA 19 1 A 0
2011 7 29 5 1424 NA CO 1079 N14628 NA NA NA -6 IAH ORD 925 NA 13 1 A 0
2011 1 26 3 1703 NA CO 410 N77296 NA NA NA 0 IAH IAD 1190 NA 13 1 B 0
2011 8 11 4 1320 NA CO 1669 N73275 NA NA NA 0 IAH MIA 964 NA NA 1 A 0
2011 7 25 1 1654 NA CO 1422 N58606 NA NA NA 24 IAH ATL 689 NA NA 1 C 0
2011 1 26 3 1926 NA CO 310 N77865 NA NA NA 26 IAH EWR 1400 NA NA 1 B 0
2011 3 31 4 1016 NA CO 586 N19136 NA NA NA 156 IAH MCO 853 NA NA 1 B 0
2011 2 8 2 1057 NA CO 408 N11641 NA NA NA 187 IAH EWR 1400 NA NA 1 A 0
2011 4 4 1 1632 NA DL 8 N600TR NA NA NA 42 IAH ATL 689 NA NA 1 A 0

Reverse the order of arranging

By default, arrange() arranges the rows from smallest to largest. Rows with the smallest value of the variable will appear at the top of the data set. You can reverse this behavior with the desc() function. arrange() will reorder the rows from largest to smallest values of a variable if you wrap the variable name in desc() before passing it to arrange().

# Arrange according to carrier and decreasing departure delays
arrange(hflights, UniqueCarrier, desc(DepDelay))  %>%
  head(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "center", font_size = 11) %>%
  row_spec(0, bold = T, color = "white", background = "#3f7689")
Year Month DayofMonth DayOfWeek DepTime ArrTime UniqueCarrier FlightNum TailNum ActualElapsedTime AirTime ArrDelay DepDelay Origin Dest Distance TaxiIn TaxiOut Cancelled CancellationCode Diverted
2011 12 12 1 650 808 AA 1740 N473AA 78 49 978 970 IAH DFW 224 14 15 0 0
2011 11 19 6 1752 1910 AA 1903 N495AA 78 40 685 677 IAH DFW 224 7 31 0 0
2011 12 22 4 1728 1848 AA 1903 N580AA 80 40 663 653 IAH DFW 224 8 32 0 0
2011 10 23 7 2305 2 AA 742 N548AA 57 39 507 525 IAH DFW 224 5 13 0 0
2011 9 27 2 1206 1300 AA 1948 N4YUAA 54 37 265 286 IAH DFW 224 10 7 0 0
2011 3 17 4 1647 1747 AA 1505 N584AA 60 41 262 277 IAH DFW 224 7 12 0 0
2011 6 21 2 955 1315 AA 466 N3FTAA 140 120 230 235 IAH MIA 964 9 11 0 0
2011 5 20 5 2359 130 AA 426 N565AA 91 70 255 234 IAH DFW 224 8 13 0 0
2011 4 19 2 2023 2142 AA 1925 N467AA 79 50 242 233 IAH DFW 224 11 18 0 0
2011 5 12 4 2133 53 AA 1294 N3AYAA 140 121 223 228 IAH MIA 964 5 14 0 0 
# Arrange flights by total delay (normal order).
arrange(hflights, (DepDelay + ArrDelay))  %>%
  head(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = F, position = "center", font_size = 11) %>%
  row_spec(0, bold = T, color = "white", background = "#3f7689")
Year Month DayofMonth DayOfWeek DepTime ArrTime UniqueCarrier FlightNum TailNum ActualElapsedTime AirTime ArrDelay DepDelay Origin Dest Distance TaxiIn TaxiOut Cancelled CancellationCode Diverted
2011 7 3 7 1914 2039 XE 2804 N12157 85 66 -70 -1 IAH MEM 468 4 15 0 0
2011 8 31 3 934 1039 OO 2040 N783SK 185 172 -56 -11 IAH BFL 1428 3 10 0 0
2011 8 21 7 935 1039 OO 2001 N767SK 184 171 -56 -10 IAH BFL 1428 3 10 0 0
2011 8 28 7 2059 2206 OO 2003 N783SK 187 171 -54 -11 IAH BFL 1428 5 11 0 0
2011 8 29 1 935 1041 OO 2040 N767SK 186 169 -54 -10 IAH BFL 1428 4 13 0 0
2011 12 25 7 741 926 OO 4591 N814SK 165 147 -57 -4 IAH SLC 1195 4 14 0 0
2011 1 30 7 620 812 OO 4461 N804SK 172 156 -49 -10 IAH SLC 1195 5 11 0 0
2011 8 3 3 1741 1810 XE 2603 N11107 89 73 -40 -19 IAH HOB 501 5 11 0 0
2011 8 4 4 930 1041 OO 1171 N715SK 191 177 -49 -10 IAH BFL 1428 4 10 0 0
2011 8 18 4 939 1043 OO 2001 N783SK 184 172 -52 -6 IAH BFL 1428 4 8 0 0

Session info

sessionInfo()
## R version 3.5.2 (2018-12-20)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 16299)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=German_Switzerland.1252  LC_CTYPE=German_Switzerland.1252   
## [3] LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C                       
## [5] LC_TIME=German_Switzerland.1252    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] hflights_0.1     ggplot2_3.1.0    dplyr_0.8.0.1    gapminder_0.3.0 
## [5] kableExtra_1.0.1 knitr_1.21      
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.0        highr_0.7         plyr_1.8.4       
##  [4] pillar_1.3.1      compiler_3.5.2    prettydoc_0.2.1  
##  [7] tools_3.5.2       digest_0.6.18     gtable_0.2.0     
## [10] evaluate_0.12     tibble_2.0.1      viridisLite_0.3.0
## [13] pkgconfig_2.0.2   rlang_0.3.1       cli_1.0.1        
## [16] rstudioapi_0.9.0  yaml_2.2.0        xfun_0.4         
## [19] withr_2.1.2       httr_1.4.0        stringr_1.4.0    
## [22] xml2_1.2.0        hms_0.4.2         webshot_0.5.1    
## [25] grid_3.5.2        tidyselect_0.2.5  glue_1.3.0       
## [28] R6_2.4.0          fansi_0.4.0       rmarkdown_1.11   
## [31] readr_1.3.1       purrr_0.3.0       magrittr_1.5     
## [34] scales_1.0.0      htmltools_0.3.6   assertthat_0.2.0 
## [37] rvest_0.3.2       colorspace_1.4-0  utf8_1.1.4       
## [40] stringi_1.3.1     lazyeval_0.2.1    munsell_0.5.0    
## [43] crayon_1.3.4